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ICRISAT Governing Board 2019 PC meeting: District Level Database for India and Interactive Web Tool-by Dr S Nedumaran and team

  1. District Level Database for India and Interactive Web Tool Program Committee Meeting of the ICRISAT Governing Board 10 April 2019 S Nedumaran, P Parthasarathy Rao and Abhishek Rathore Research program on Innovation Systems for the Drylands (ISD)
  2. ICRISAT has started collating meso level database (country, state and district level) since 1980’s covering 7 states initially, later expanded to 10 states in 1990’s Since 1997, the data was updated under the following projects:  Sustainable Rainfed Agricultural project funded by the World Bank  Mixed Crop-Livestock Systems funded by SLP  VDSA project funded by BMGF (2009-2014)  Currently under a project jointly supported by Tata Cornell Institute on Nutrition and Agriculture (TCI) and ICRISAT (Since May 2018) Meso level database Development for India at ICRISAT 20 States from 1966-2015 20 States and 571 districts
  3. Core VariablesAgriculture • Area and Production: Cereals, Pulses, Oilseeds and cash Crops • Irrigated Area (crop and source) • HYV Area • Land Use (Geographical Area, Forest Area, cropped area etc.) • Farm Harvest Prices • Fertilizer Consumption and prices Socio-economicandInfra • Field Labor Wages • Population Census Data (Population, literacy, cultivators, agric. laborers) • Livestock (Census Data) • Operational Holdings • Markets and Roads • Farm Implements and Machinery Environment • Annual and Monthly Actual Rainfall • Annual and Monthly Normal Rainfall, Length of Growing Period, Soil Type (one point of time)
  4. Additional Variables • Soft infrastructure related to education, banks, etc. • Primary sector credit • GDP by sectors • Health and nutrition • Disaggregated F&V area and production New Data Source • Pixel level data to DLD (AET, PET, temperature, rainfall, soil moisture, etc.) – source: terraclimate • Remote sensing (Irrigated area) Exploring new data and sources Example: 2016 Actual Evapotranspiration (AET) (mm) Pixel to DLD
  5. Organization of DLD Unapportioned data 1990-2015 All districts (571) Cross section Analysis Digitized Maps for spatial and temporal analysis Apportioned data 1966/2001-2015 Districts with 1966 (311) and 2001 (500) boundaries Cross section and Time-series analysis Structure of the database Odisha – 1966 (13 districts) Odisha – 2016 (30 districts)
  6.  Rainfed agriculture/Crop livestock typology classification for India  Outlook report for mandate crops  Diversification of agriculture and factors driving change  Drivers of adoption of improved technology (HYVs, crossbreeding, mechanization)  Aggregate/crop supply response studies  Crop-livestock interactions and feed dynamics  Role of infrastructure and market access in agricultural productivity  Climate change impacts at regional scale  Nutrition outcomes Research Activities and Users of District level Database The main users:  ICRISAT research programs  Other CG institutes: IFPRI, IWMI, CIMMYT, ILRI  ARIs and Universities: Yale University (USA), Cornel University (USA), World Bank, Hitoba University (Japan), ISEC - Bangalore, CESS - Hyderabad, ICAR and its institutions (CRIDA, NIAP)  Researchers and students for their PhD and Master’s level thesis  Donor organizations: Gates Foundation, ICAR, IFAD, World bank, USAID
  7. Example of Nutritional Indicators Source: NHFS-4 (2015-16)
  8.  World Bank. 2014. Republic of India : Accelerating Agricultural Productivity Growth. Washington, DC. © World Bank: http://documents.worldbank.org/curated/en/587471468035437545/pdf/880930REVISED00ivity0Growth00PUBLIC.pdf  Cornell University, 2015. Agricultural Policy and Nutrition Outcomes – Getting beyond the preoccupation with staple grains: https://link.springer.com/article/10.1007/s12571-015-0461-x  GOI, 2018. Economic Survey: http://mofapp.nic.in:8080/economicsurvey/pdf/082- 101_Chapter_06_ENGLISH_Vol_01_2017-18.pdf  Climate Change:  ICRISAT, 2015. Vulnerability and resilience to climate change: https://www.amazon.com/dp/B0193CC134/ref=rdr_kindle_ext_tmb  NIAP (ICAR), 2019. Crop diversification and resilience of agriculture to climatic shocks: https://doi.org/10.1016/j.agsy.2019.03.005 Some recent Reports using District-level Database
  9. Data Visualization Processing and aggregation Lots and lots of data Better Information = BI = Business Intelligence  Data access from anywhere  Search based data discovery  Download Data  Create Dashboards  Visual-Spatial Intelligence  Metadata Management Why Web tool?
  10. Release of Web tool (Beta version). URL link…. (yet to add…)
  11. Web tool and exploring new data sources • Additional features – spatial maps; states and district dashboards (ongoing) • Exploring new data sources (ongoing) • Maintenance of web – with support from DMU • Exploring RS data Data collection and update • Collate and update continuously - online data source • Periodic update (once in 2 years) – soft and hardcopy publications Strategies to mobilise funds • Popularize the database – using SMC and social media • Highlight key research insights to donors, CG institutes, and ARI • Approaching donors using key contact points Way forward… To keep the data live – request MG to provide support from strategic funds, CRPs, Bigdata platform
  12. Donors and Partners Acknowledgement Team members & Contributors ICRISAT: S Nedumaran R Padmaja Shalander Kumar P Jyosthnaa E Jagadeesh Irshad Ahmed Ismail Mohammed Abhishek Rathore S Chaitanya Arabinda Padhee TCI: Andaleeb Rahman Kiera Crowley Consultant and Mentor: P Parthasarathy Rao (Ex - ICRISAT) Our thanks to all central and state Government departments for providing access to the data and publications
  13. Thank You
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